#include <stdio.h>
#include <stack>
#include <opencv2/opencv.hpp>
#include <iostream>
#include <fstream>

using namespace cv;
using namespace std;

int main()
{
    ifstream fin("calibdata.txt"); /* 标定所用图像文件的路径 */
    ofstream fout("caliberation_result.txt");  /* 保存标定结果的文件 */
    //读取每一幅图像，从中提取出角点，然后对角点进行亚像素精确化
    cout<<"开始提取角点………………";
    int image_count=0;  /* 图像数量 */
    Size image_size;  /* 图像的尺寸 */
    Size board_size = Size(9,6);    /* 标定板上每行、列的角点数 */
    vector<Point2f> image_points_buf;  /* 缓存每幅图像上检测到的角点 */
    vector< vector<Point2f> > image_points_seq; /* 保存检测到的所有角点 */
    string filename;
    int count= -1 ;//用于存储角点个数。
    while (getline(fin,filename))
    {
        image_count++;
        // 用于观察检验输出
        cout<<"image_count = "<<image_count<<endl;
        /* 输出检验*/
        cout<<"-->count = "<<count;
        Mat imageInput=imread(filename);
        if (image_count == 1)  //读入第一张图片时获取图像宽高信息
        {
            image_size.width = imageInput.cols;
            image_size.height =imageInput.rows;
            cout<<"image_size.width = "<<image_size.width<<endl;
            cout<<"image_size.height = "<<image_size.height<<endl;
        }

        /* 提取角点 */
        if (0 == findChessboardCorners(imageInput,board_size,image_points_buf))
        {
            cout<<"can not find chessboard corners!\n"; //找不到角点
            exit(1);
        }
        else
        {
            Mat view_gray;
            cvtColor(imageInput,view_gray,CV_RGB2GRAY);
            /* 亚像素精确化 */
            find4QuadCornerSubpix(view_gray,image_points_buf,Size(11,11)); //对粗提取的角点进行精确化
            image_points_seq.push_back(image_points_buf);  //保存亚像素角点
            /* 在图像上显示角点位置 */
            drawChessboardCorners(view_gray,board_size,image_points_buf,true); //用于在图片中标记角点
            imshow("Camera Calibration",view_gray);//显示图片
            waitKey(500);//暂停0.5S
            //waitKey(100);//暂停0.5S
        }
    }
    int total = image_points_seq.size();
    cout<<"total = "<<total<<endl;
    int CornerNum=board_size.width*board_size.height;  //每张图片上总的角点数
    for (int ii=0 ; ii<total ;ii++)
    {
        if (0 == ii%CornerNum)// 24 是每幅图片的角点个数。此判断语句是为了输出 图片号，便于控制台观看
        {
            int i = -1;
            i = ii/CornerNum;
            int j=i+1;
            cout<<"--> 第 "<<j <<"图片的数据 --> : "<<endl;
        }
        if (0 == ii%3)  // 此判断语句，格式化输出，便于控制台查看
        {
            cout<<endl;
        }
        else
        {
            cout.width(10);
        }
        //输出所有的角点
        cout<<" -->"<<image_points_seq[ii][0].x;
        cout<<" -->"<<image_points_seq[ii][0].y;
    }
    cout<<"角点提取完成！\n";

    //以下是摄像机标定
    cout<<"开始标定………………";
    /*棋盘三维信息*/
    Size square_size = Size(3,3);  /* 实际测量得到的标定板上每个棋盘格的大小 */
    vector< vector<Point3f> > object_points; /* 保存标定板上角点的三维坐标 */
    /*内外参数*/
    Mat cameraMatrix=Mat(3,3,CV_32FC1,Scalar::all(0)); /* 摄像机内参数矩阵 */
    vector<int> point_counts;  // 每幅图像中角点的数量
    Mat distCoeffs=Mat(1,5,CV_32FC1,Scalar::all(0)); /* 摄像机的5个畸变系数：k1,k2,p1,p2,k3 */
    vector<Mat> tvecsMat;  /* 每幅图像的旋转向量 */
    vector<Mat> rvecsMat; /* 每幅图像的平移向量 */
    /* 初始化标定板上角点的三维坐标 */
    int i,j,t;
    for (t=0;t<image_count;t++)
    {
        vector<Point3f> tempPointSet;
        for (i=0;i<board_size.height;i++)
        {
            for (j=0;j<board_size.width;j++)
            {
                Point3f realPoint;
                /* 假设标定板放在世界坐标系中z=0的平面上 */
                realPoint.x = i*square_size.width;
                realPoint.y = j*square_size.height;
                realPoint.z = 0;
                tempPointSet.push_back(realPoint);
            }
        }
        object_points.push_back(tempPointSet);
    }
    /* 初始化每幅图像中的角点数量，假定每幅图像中都可以看到完整的标定板 */
    for (i=0;i<image_count;i++)
    {
        point_counts.push_back(board_size.width*board_size.height);
    }
    /* 开始标定 */
    calibrateCamera(object_points,image_points_seq,image_size,cameraMatrix,distCoeffs,rvecsMat,tvecsMat,0);
    cout<<"标定完成！\n";
    //对标定结果进行评价
    cout<<"开始评价标定结果………………\n";
    double total_err = 0.0; /* 所有图像的平均误差的总和 */
    double err = 0.0; /* 每幅图像的平均误差 */
    vector<Point2f> image_points2; /* 保存重新计算得到的投影点 */
    cout<<"\t每幅图像的标定误差：\n";
    fout<<"每幅图像的标定误差：\n";
    for (i=0;i<image_count;i++)
    {
        vector<Point3f> tempPointSet=object_points[i];
        /* 通过得到的摄像机内外参数，对空间的三维点进行重新投影计算，得到新的投影点 */
        projectPoints(tempPointSet,rvecsMat[i],tvecsMat[i],cameraMatrix,distCoeffs,image_points2);
        /* 计算新的投影点和旧的投影点之间的误差*/
        vector<Point2f> tempImagePoint = image_points_seq[i];
        Mat tempImagePointMat = Mat(1,tempImagePoint.size(),CV_32FC2);
        Mat image_points2Mat = Mat(1,image_points2.size(), CV_32FC2);
        for (int j = 0 ; j < tempImagePoint.size(); j++)
        {
            image_points2Mat.at<Vec2f>(0,j) = Vec2f(image_points2[j].x, image_points2[j].y);
            tempImagePointMat.at<Vec2f>(0,j) = Vec2f(tempImagePoint[j].x, tempImagePoint[j].y);
        }
        err = norm(image_points2Mat, tempImagePointMat, NORM_L2);
        total_err += err/=  point_counts[i];
        std::cout<<"第"<<i+1<<"幅图像的平均误差："<<err<<"像素"<<endl;
        fout<<"第"<<i+1<<"幅图像的平均误差："<<err<<"像素"<<endl;
    }
    std::cout<<"总体平均误差："<<total_err/image_count<<"像素"<<endl;
    fout<<"总体平均误差："<<total_err/image_count<<"像素"<<endl<<endl;
    std::cout<<"评价完成！"<<endl;
    //保存定标结果
    std::cout<<"开始保存定标结果………………"<<endl;
    Mat rotation_matrix = Mat(3,3,CV_32FC1, Scalar::all(0)); /* 保存每幅图像的旋转矩阵 */
    fout<<"相机内参数矩阵："<<endl;
    fout<<cameraMatrix<<endl<<endl;
    fout<<"畸变系数：\n";
    fout<<distCoeffs<<endl<<endl<<endl;
    for (int i=0; i<image_count; i++)
    {
        fout<<"第"<<i+1<<"幅图像的旋转向量："<<endl;
        fout<<tvecsMat[i]<<endl;
        /* 将旋转向量转换为相对应的旋转矩阵 */
        Rodrigues(tvecsMat[i],rotation_matrix); //a bug
        fout<<"第"<<i+1<<"幅图像的旋转矩阵："<<endl;
        fout<<rotation_matrix<<endl;
        fout<<"第"<<i+1<<"幅图像的平移向量："<<endl;
        fout<<rvecsMat[i]<<endl<<endl;
    }
    std::cout<<"完成保存"<<endl;
    fout<<endl;
    system("pause");
    return 0;
}
